@jvikoren using the legacy optimizer should work in this case, see here: https://www.tensorflow.org/api_docs/python/tf/keras/optimizers/legacy/Optimizer import tensorflow as tf from tensorflow.keras.optimizers.legacy import Adam cifar = tf.keras.datasets.cifar100 (x_train, y_train), (x_test, y_test) = cifar.load_data() model = tf.keras.applications.ResNet50( include_top=True, weights=None, input_shape=(32, 32, 3), classes=100,) loss_fn = tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True) # Instantiate legacy Adam optimizer model.compile(optimizer=Adam(), loss=loss_fn, metrics=["accuracy"]) model.fit(x_train, y_train, epochs=5, batch_size=64) Works for me on M1 Air with a fresh version of miniconda.